In computer vision and other imaging and computing contexts, depth images are generated based on two (e.g., left and right or reference and target) captured images of a scene. In particular, in a stereo-depth camera, depth is determined primarily from solving the correspondence problem between left and right images of a scene, determining the disparity for each pixel (i.e., a shift between object points in the left and right images), and calculating the depth map from disparity using triangulation techniques.
In active stereo vision, an infrared (IR) pattern is projected onto a scene such that the images obtained during exposure include the IR pattern as modified by the scene. Such techniques may be advantageous when the scene itself does not include a lot of texture (e.g., for blank white walls or similar scene elements). The obtained images including the IR texture are then used to generate a depth image using stereoscopic image matching techniques based in part on the features of the modified IR pattern. Such depth image(s) are used in a wide variety of computer vision and image processing contexts.
Current IR patterns and projectors have shortcomings with respect to the resultant stereoscopic matching and depth image results. It is with respect to these and other considerations that the present improvements have been needed. Such improvements may become critical as the desire to utilize depth images in a variety of applications becomes more widespread.